Plotly

plot_ly(dfmodel, x=~food,color=~dish)

## No trace type specified:
##   Based on info supplied, a 'histogram' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#histogram

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

plot_ly(dfmodel, x=~casserole, y=~mean,color=~food)

## No trace type specified:
##   Based on info supplied, a 'bar' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#bar

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

food <- ggplot(dfmodel,aes(x=mean,fill=food, frame=before_or_after, alpha=.07)) +
  geom_density()

ggplotly(food)

dish <- ggplot(dfmodel,aes(x=mean,fill=dish, frame=before_or_after, alpha=.07)) +
  geom_density()

ggplotly(dish)

argued <- ggplot(dfmodel,aes(x=mean,fill=argued, frame=before_or_after, alpha=.07)) +
  geom_density()

ggplotly(argued)

test2 <- ggplot(dfmodel,aes(x=casserole,y=mean, fill=casserole))+
  geom_boxplot()#+
  geom_point(aes(x=mean))

## mapping: x = ~mean 
## geom_point: na.rm = FALSE
## stat_identity: na.rm = FALSE
## position_identity

ggplotly(test2)

library(ggridges)
ggplot(dfmodel,aes(y=casserole,x=mean, fill=casserole))+
geom_density_ridges() 

## Picking joint bandwidth of 0.305